Limits on Fundamental Limits to Computation

An indispensable part of our lives, computing has also become essential to industries and governments. Steady improvements in computer hardware have been supported by periodic doubling of transistor densities in integrated circuits over the last fifty years. Such Moore scaling now requires increasingly heroic efforts, stimulating research in alternative hardware and stirring controversy. To help evaluate emerging technologies and enrich our understanding of integrated-circuit scaling, we review fundamental limits to computation: in manufacturing, energy, physical space, design and verification effort, and algorithms. To outline what is achievable in principle and in practice, we recall how some limits were circumvented, compare loose and tight limits. We also point out that engineering difficulties encountered by emerging technologies may indicate yet-unknown limits.Comment: 15 pages, 4 figures, 1 tabl

Promoting the Readiness of Minors in Supplemental Security Income (PROMISE) [CFDA 84.418P]

Over the past two decades, New York State (NYS) has been actively and collaboratively engaged in systems change across three primary domains: 1) to develop a comprehensive employment system to reduce barriers to work and improve employment outcomes of individuals with disabilities; 2) to enhance the post-school adult outcomes of youth with disabilities, by collaboratively advancing evidence-based secondary transition practices at the regional, school district and individual student levels; and, 3) to support the return-to-work efforts of individuals with disabilities who receive Social Security Administration (SSA) disability benefits under the Supplemental Security Income (SSI) program and Social Security Disability Insurance (SSDI). These domains have been supported by numerous federal and state initiatives including: the US Department of Education’s Office of Special Education and Rehabilitation Services (OSERS)-sponsored Transition Systems Change grant; the SSA-sponsored State Partnership Initiative (NYWORKS); two Youth Transition Demonstrations (YTD); the Benefits Offset National Demonstration (BOND); and, three cycles of funding for the National Work Incentives Support Center (WISC); the US Department of Labor (DOL)-sponsored Work Incentive Grant, Disability Program Navigator Initiative, and Disability Employment Initiative; three rounds of funding from the Center for Medicaid and Medicare Services (CMS) for Medicaid Infrastructure Grants (MIG, NY Makes Work Pay); the NYS Education Department (NYSED) sponsored Model Transition Program (MTP); and three multi-year cycles of the statewide Transition Coordination Site network. Most recently, NYS has sponsored the Statewide Transition Services Professional Development Support Center (PDSC); the NYS Developmental Disability Planning Council (DDPC)-sponsored Transition Technical Assistance Support Program (T-TASP), NYS Work Incentives Support Center (NYS WISC), and NYS Partners in Policy Making (PIP); the NYS Office of Mental Health (OMH)-sponsored Career Development Initiative; and others. The growing statewide and gubernatorial emphasis on employment for New Yorkers with disabilities developed over the past two decades stemming from these initiatives, supported by service innovations and shared vision across state agencies and employment stakeholders, establishes a strong foundation for implementing and sustaining a research demonstration to “Promote the Readiness of Minors in Supplemental Security Income” (PROMISE). The NYS PROMISE will build upon NYS’ past successes and significantly support NYS in removing systems, policy and practice barriers for transition-age youth who receive SSI and their families. The NYS OMH through the Research Foundation for Mental Hygiene (RFMH), with their management partners the New York Employment Support System (NYESS) Statewide Coordinating Council (SCC) and Cornell University Employment and Disability Institute, along with the proposed research demonstration site community, join the NYS Governor’s Office in designing and implementing a series of statewide strategic service interventions to support the transition and employment preparation of youth ages 14-16 who receive SSI

Neurons and symbols: a manifesto

We discuss the purpose of neural-symbolic integration including its principles, mechanisms and applications. We outline a cognitive computational model for neural-symbolic integration, position the model in the broader context of multi-agent systems, machine learning and automated reasoning, and list some of the challenges for the area of neural-symbolic computation to achieve the promise of effective integration of robust learning and expressive reasoning under uncertainty

Visualizing Fantasy Fiction: Design of a Class in Digital Scholarship and Visualization, including Research, Organization and Digital Visualization, that Does Not Require Programming or IT support

This paper outlines a course to integrate digital visualizations into undergraduate research. These visualizations will include mapping and timelines of events, and the ability to hyperlink the events, characters, and story lines in a fantasy fiction story such as Lord of the Rings or A Game of Thrones. The digital scholarship will involve the methodology for collecting, organizing, and representing the data for the visualizations. The topic for the visualizations in this paper is fantasy fiction; however the methods to develop these visualizations will be applicable to many academic disciplines, including the humanities and social sciences. The paper outlines the justification for this class, the appropriate audience for this class, and the tools needed. Types of projects and homework assignments to implement the visualizations are suggested. It concludes with a syllabus outlining a typical schedule for this class

An abstract machine based execution model for computer architecture design and efficient implementation of logic programs in parallel.

The term "Logic Programming" refers to a variety of computer languages and execution models which are based on the traditional concept of Symbolic Logic. The expressive power of these languages offers promise to be of great assistance in facing the programming challenges of present and future symbolic processing applications in Artificial Intelligence, Knowledge-based systems, and many other areas of computing. The sequential execution speed of logic programs has been greatly improved since the advent of the first interpreters. However, higher inference speeds are still required in order to meet the demands of applications such as those contemplated for next generation computer systems. The execution of logic programs in parallel is currently considered a promising strategy for attaining such inference speeds. Logic Programming in turn appears as a suitable programming paradigm for parallel architectures because of the many opportunities for parallel execution present in the implementation of logic programs. This dissertation presents an efficient parallel execution model for logic programs. The model is described from the source language level down to an "Abstract Machine" level suitable for direct implementation on existing parallel systems or for the design of special purpose parallel architectures. Few assumptions are made at the source language level and therefore the techniques developed and the general Abstract Machine design are applicable to a variety of logic (and also functional) languages. These techniques offer efficient solutions to several areas of parallel Logic Programming implementation previously considered problematic or a source of considerable overhead, such as the detection and handling of variable binding conflicts in AND-Parallelism, the specification of control and management of the execution tree, the treatment of distributed backtracking, and goal scheduling and memory management issues, etc. A parallel Abstract Machine design is offered, specifying data areas, operation, and a suitable instruction set. This design is based on extending to a parallel environment the techniques introduced by the Warren Abstract Machine, which have already made very fast and space efficient sequential systems a reality. Therefore, the model herein presented is capable of retaining sequential execution speed similar to that of high performance sequential systems, while extracting additional gains in speed by efficiently implementing parallel execution. These claims are supported by simulations of the Abstract Machine on sample programs